High resolution microprice estimates from limit orderbook data using hyperdimensional vector Tsetlin Machines
Trading and Market Microstructure
2024-11-22 v1 Machine Learning
Statistical Finance
Abstract
We propose an error-correcting model for the microprice, a high-frequency estimator of future prices given higher order information of imbalances in the orderbook. The model takes into account a current microprice estimate given the spread and best bid to ask imbalance, and adjusts the microprice based on recent dynamics of higher price rank imbalances. We introduce a computationally fast estimator using a recently proposed hyperdimensional vector Tsetlin machine framework and demonstrate empirically that this estimator can provide a robust estimate of future prices in the orderbook.
Keywords
Cite
@article{arxiv.2411.13594,
title = {High resolution microprice estimates from limit orderbook data using hyperdimensional vector Tsetlin Machines},
author = {Christian D. Blakely},
journal= {arXiv preprint arXiv:2411.13594},
year = {2024}
}